Below are the first 10 and last 10 pages of uncorrected machine-read text (when available) of this chapter, followed by the top 30 algorithmically extracted key phrases from the chapter as a whole.
Intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text on the opening pages of each chapter. Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages.
Do not use for reproduction, copying, pasting, or reading; exclusively for search engines.
OCR for page 40
41 CHAPTER FOUR FACTORS AND CIRCUMSTANCES AFFECTING PUBLIC OPINION Today, traffic congestion is perceived as one of the most press- data and may render the data less representative of the universe ing problems in high density or high growth areas. Addressing of all surveys on these topics. Furthermore, we recognize that this issue generally involves some type of improvement in the results from the different surveys may have been measured roadway infrastructure or capacity. Tolls and road pricing are on different scales and with different analysis designs. At the interrelated with such solutions because of reliance on tolls same time, great care was taken in the development of the as financing tools, and road pricing as traffic demand man- sample of public opinion data presented in chapter three. We agement tools. We have now reached the situation where the sampled for diversity, including a broad and diverse range major constraint on the successful implementation of tolling of public opinion studies and used snowball sampling tech- and road pricing relates largely to policy making (i.e., lack of niques to uncover rare or hard-to-find research studies. Have stakeholder and political acceptability) rather than to techni- we represented the population well? It is hard to know how cal or administrative barriers. Examinations of historical data well we have done because a perfect listing of the universe in fields outside of transportation have found a strong link does not exist. That said, and with consideration of the caveats between policy making and public opinion. Two separate associated with analyzing these data, we examined the gen- studies found that in two-thirds of cases in which a proposed eral patterns of support and opposition to pricing according policy change resulted in legislative action, that action was in to various factors and contexts using the poll or survey data the direction preferred by majority public opinion (120,121). only. Also we have factored out the results related to tax- related initiatives in the following analyses. Prior empirical research in transportation indicates that public acceptance of tolls and road pricing is low--in spite of the perception of traffic problems as serious (1,6,122,123). Methodological Factors These prior studies did not have the broad set and more recent Given that there is a link between policy making and public data points of this synthesis from which to draw conclusions. opinion, the quality of public opinion data is critical. A poorly With this information, it is possible to identify the factors and administered poll or inaccurate survey can misrepresent actual circumstances that affect public opinion, to examine trends in public opinion and, in turn, influence future policy debates. A public opinion, and to derive crucial implications for future poll or survey is a method of gathering information from a policy and planning in this area. sample of individuals within a particular group or population. This information is then used to draw conclusions about the PUBLIC OPINION ON PRICING entire group or population. The key to a representative survey is that the chance (or probability) of every unit (or individual) Our review indicates that in the aggregate there is majority in the population being selected for the sample must be known support for tolling and road pricing. Among all the surveys and properly accounted for in the analysis of the results. If presented in chapter three, 56% indicated support for tolling a sample is drawn by convenience, intercept, or other non- or road pricing concepts (see Table 1). Opposition was encoun- random methods, the resulting data are not governed by prob- tered in 31% of cases, and mixed results (i.e., no majority ability theory. The data represent only the narrow slice of the support or opposition) occurred in 13% of cases. The level of group or population that was surveyed. aggregate support for road pricing contrasts sharply with that found for tax-related initiatives. The aggregate level of sup- A survey is also different from a focus group. Focus groups port for tax-related initiatives was 27%, with 60% opposed typically have eight to ten participants and therefore it would and 13% mixed. take many groups to build up a significant sample size. More importantly, focus group participants are rarely sampled by The results in Table 1 were derived by coding each of the probability methods. Typically, they are recruited from a data- surveys presented in chapter three on a 5-point scale of support base or intercept methods. Focus groups may provide inter- or opposition (i.e., strongly support, support, mixed, oppose, esting insight for certain purposes, but they cannot be used strongly oppose). Is this valid? We acknowledge that the sam- to draw inferences about the larger population. Therefore, ple of surveys is small and it was not randomly generated. focus group results have not been included in our analyses The outcomes of a few surveys can have a big effect on the of public opinion trends and patterns presented in this section.
OCR for page 41
42 TABLE 1 ate" validity, and 16% were coded as "low." We found public PUBLIC OPINION ON PRICING VERSUS support for tolling in 59% of the studies coded as "high" valid- TAX-RELATED INITIATIVES ity, compared with 61% of the "moderate" validity and 38% of Tolling or Road Pricing Tax-Related Initiative the "low" validity cases. This finding adds credence to the gen- Majority Support 57% 27% eral finding of majority support for tolling and road pricing. Majority Opposition 31% 60% Neither Majority 13% 13% Total Percent 100% 100% Differences in aggregate results were found based on the Total Cases 103 15 sponsor of the poll or survey. When the poll or survey was sponsored by a tolling entity or agency responsible for the project, support was significantly higher in the aggregate (70%) Several factors can affect the accuracy of survey results. than opposition (22%). Aggregate support was higher than Groves provided an excellent overview of the components of opposition in media-sponsored polls but by a smaller margin survey quality in which he classified errors in surveys into (54% to 46%). When it was sponsored by another organization four main types (124): (i.e., university or association), aggregate support (47%) was below the majority threshold, but still higher than opposition · Coverage errors, referring to the exclusion of some (34%). Mixed results (i.e., neither clear support nor opposition) members of the study population from the sample frame. were highest among surveys sponsored by organizations other · Sampling errors, indicating the estimating quality of sam- than sponsoring agency (19%), followed by the media (8%). In ple statistics that are primarily a consequence of sample surveys sponsored by the tolling or road pricing entity, there sizes and sample design. was either clear majority support or majority opposition. · Non-response errors, when certain individuals selected in a sample do not participate in the survey or fail to Polling and sponsoring agencies have a choice in the selec- answer an item in the interview. tion of the respondents to be surveyed or interviewed. This · Measurement errors, relating to the discrepancy between analysis indicates that support and opposition vary depending an individual's true opinions and the individual's on the type of respondent pool selected. For data representa- responses in a survey interview. tive of "potential users," aggregate support was significantly higher (74%) than opposition (15%). A similar outcome was The first two sources of error can be controlled through observed with public opinion measures of registered voters-- the way in which the sampling frame has been selected and support was found in 71% of cases and opposition in 24%. the sample has been designed, and the latter two sources are However, for those polls or surveys that targeted the general intrinsically linked to the quality of the survey execution and public, a different pattern was observed. In these latter polls, the instrument design (125127). Awareness of these errors support and opposition were equal in proportion at 42% each. and their sources is a way to identify surveys that have not The mixed results were highest among surveys of the general been conducted scientifically. Such surveys include "opt-in" public (16%), followed by potential users (11%), and then surveys in which respondents select themselves. Examples registered voters (5%). are polls on the Internet where visitors to websites are asked to vote on one issue or another. Push polls are another type of Most of the polls or surveys did not include clarifying or fake survey. A push poll is where, using the guise of opinion additional information in the question wording that might polling, disinformation about a candidate or issue is planted influence public opinion. However, support was higher when in the minds of those being surveyed. Push polls are designed this information was presented to respondents as part of the to shape, rather than measure, public opinion. Although there survey question, such as "would you support congestion if are many potential sources of error, surveys that are conducted the money were used to prevent an increase in mass transit according to sound scientific methods can provide highly fares and bridge and tunnel tolls?" Support for tolling was accurate insights into public opinions. noted in 94% of these cases when additional information was provided, compared with 48% of cases in which no addi- Understanding that the samples are small and that the char- tional information was presented as part of the survey ques- acteristics of the public opinion data differ significantly, inter- tion. Higgins reached this same conclusion in his article on esting findings in the level of support or opposition can be public polling and congestion pricing (128). He points out explained by methodology factors, including the validity of that when congestion pricing is simply described as a way to the research, its sponsor, the survey population, and question reduce congestion with no other information, support is low. wording. However, that support increases when the definition provides clarifying information or a description of benefits. Assessing the validity of the surveys presented in chapter three without full access to the documentation is challenging. However, available information, primarily sample size and Project- or Issue-Related Characteristics sample type, were used to rate the validity of each survey. Nearly half (54%) of the polls or surveys were coded as hav- Our compiled public opinion data also supported analysis of ing "high" validity, about one-third (30%) as having "moder- differences in public opinion results based on project- or
OCR for page 42
43 TABLE 2 PUBLIC OPINION BASED ON TYPE OF PRICING Cordon PublicPrivate Express Toll Traditional Toll Tolling Partnership Lanes Road HOT Lanes Majority Support 32% 0% 62% 71% 73% Majority Opposition 53% 60% 23% 26% 15% Neither Majority 16% 40% 15% 3% 12% Total Percent 100% 100% 100% 100% 100% Total Cases 19 10 13 35 26 issue-related characteristics, such as type of pricing, year, The number of cases in these two time periods differed sig- and context. nificantly, with 27 public opinion polls or surveys before 2002 and 76 afterward. This increase in the number of surveys or Most of the surveys and polls compiled in this synthesis polls is indicative of the growing interest in tolling and road report (63%) were done in association with a specific project pricing as solutions for financing or congestion challenges. The (i.e., pre- and post-surveys to evaluate the impact of the I-394 drop-off in support may be associated with the type of pricing MnPass Lanes in Minneapolis, Minnesota). Other times public that was referenced in the public opinion research. The early opinion was elicited in a general public opinion survey on mul- surveys were done in association with the early cordon or area tiple issues (i.e., citizen survey for the Collier County, Florida pricing experiments. In the mid-1990s to 2002, the types of government). Public opinion was more supportive when a spe- projects being considered were traditional toll roads, express cific project or concept was targeted (62% of cases) versus gen- toll lanes, and HOT lanes. In more recent years, cordon tolling eral questioning on tolling or road pricing (48% of cases). and PPP projects have been brought into the public sphere. Level of support or opposition varied according to the One way of disentangling the trend data is to examine type of project on which public opinion was solicited (see individual projects. Table 3 presents the trend data that were Table 2). The notable standouts are cordon pricing and PPPs, compiled in chapter three for several different types of proj- both of which show higher opposition than support. Support ects in different geographic areas. These trend data need to was present in 32% of cordon tolling cases, and none of the be considered carefully because they represent surveys con- PPP cases. Although support was higher than opposition for ducted by different polling or survey agencies of different HOT lanes, express toll lanes, and toll roads, different pat- survey populations, representing different sample sizes and terns were found. Aggregate support was evidenced in 73% sampling approaches. Also, the manner in which the ques- of HOT lane cases, 71% of toll road cases, and 62% of express tions were asked was not always the same across the surveys. toll lane cases. The spread between support and opposition Given all these caveats, there are still interesting findings. was largest in the toll road surveys. For a toll road that had yet to be built--the Foothill South Extension--public opinion was generally very stable across Discussing trends in support and opposition is challenging years--with support ranging from 54% to 59%. Clear major- because the sample sizes for any given year were quite small. ity support for the express toll lanes and HOT lanes projects In Figure 1 we have identified in parentheses the number of continued after the roads began operation (SR 91, I-15, I-394). polls or surveys that were available for analysis by year. With In Utah, where HOT lanes had not yet been built, support these caveats in mind, we found a rise in support for pricing increased nearly 5 percentage points to the level of the support in the mid-1990s and a drop-off in support starting in 2002. for the operating HOT lane projects. Support averaged 70% of those cases before 2002. Subse- quent to 2002, support averaged 49% of cases. In addition, In London, support for area charging increased after the public opinion was much more polarized before 2003. project was implemented. In New York City without area 100% 80% 60% 40% 20% 0% <1998 (8) 1998-1999 (9) 2000-2001 (10) 2002-2003 (19) 2004-2005 (23) 2006-2007 (34) Majority Support No Majority Support FIGURE 1 Trends in support versus opposition to pricing.
OCR for page 43
44 TABLE 3 PUBLIC OPINION TRENDS FOR INDIVIDUAL PROJECTS Majority Project Majority Support Opposition No Majority Orange County, California--Foothill South Extension 1999--Transportation corridor agencies 75% Not reported Not reported 2001a--Transportation corridor agencies 54% Not reported 39% 2001--Public Policy Institute of California 59% 26% 15% a 2002 --Transportation corridor agencies 58% 36% 5% 2003a--Transportation corridor agencies 53% Not reported Not reported 2004a--Transportation corridor agencies 57% 37% Not reported 20051--Transportation corridor agencies 57% 37% 6% Orange and Los Angeles Counties--SR 91 ETL 1995--California Polytechnic State University 62%68% Not reported Not reported 1996--California Polytechnic State University 60%82% Not reported Not reported 19961997--California Polytechnic State University 60%81% Not reported Not reported 1999--California Polytechnic State University 50%75% Not reported Not reported San Diego, California--I-15 HOT Lanes 1996--SANDAG 66% Not reported Not reported 1997--Wave 1: San Diego State University Foundation for SANDAG 56%95% Not reported Not reported 1998--Wave 2: San Diego State University Foundation for SANDAG 64%94% Not reported Not reported 1999--Wave 4: San Diego State University Foundation for SANDAG 58%88% Not reported Not reported 1999--Wave 5: San Diego State University Foundation for SANDAG 70%88% Not reported Not reported 2001--SANDAG 66% 28% Not reported 2005-- SANDAG 58% 14% Not reported Minneapolis, Minnesota--I-394 MnPASS HOT Lanes 2004--Humphrey Institute, Univ. of Minnesota 63% 27% 10% 2005--Humphrey Institute, Univ. of Minnesota 59% 29% 12% 2006--Humphrey Institute, Univ. of Minnesota 65% 22% 13% Salt Lake City, Utah--HOT Lanes 2005--Utah Department of Transportation 56% Not reported Not reported 2006--Utah Department of Transportation 61% Not reported Not reported London, England--Area Charging 1999--Government Office for London 53% 36% 11% 2006--Transport for London 60% Not reported Not reported New York City--Area Charging 2006--Tri-State Transportation Campaign 44% 45% 12% 2007--Quinnipiac University Poll (January) 31% 62% 7% 2007--Quinnipiac University Poll (June) 31% 52% 17% Statewide New Jersey--Lease to Private Interests 2007--AAA Mid-Atlantic Chapter (February) 20% 56% 24% 2007--RutgersEagleton Poll (August) Not reported 61% Not reported Statewide Pennsylvania--Lease to Private Interests 2007--Quinnipiac University Poll (May) 44% 42% 14% 2007--Quinnipiac University Poll (August) 40% 47% 13% a Public opinion after pro/con arguments for extending the highway have been presented to respondents as part of the interview. SANDAG = San Diego Association of Governments; ETL = express toll lane.